Find what's failing and why: review and issues for AI capabilities

Axiom has introduced a new feature called Review and Issues, designed to streamline the process of identifying and addressing problems in AI-generated outputs by utilizing a queue-based workflow for reviewing conversations. Reviewers work through conversations, making binary judgments on their quality and documenting observations in their own words, which Axiom then uses to match with existing issues or create new ones without predefined categories. This process allows domain experts to capture nuanced insights that automated systems might miss, such as incorrect actions or outdated references. The tool builds a taxonomy of issues naturally from these reviews, logging every categorization decision for traceability and correction if necessary. Over time, the system helps teams identify recurring patterns, such as specific tool integrations causing incomplete actions, thereby guiding where to focus testing and improvements. The introduction of this feature completes a comprehensive toolkit that includes capability instrumentation, test case evaluations, production feedback collection, and live traffic scoring, thereby enhancing the ability to manage and resolve AI-related issues effectively.

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